We will now fit our stocks data of the upper tail beyond the chosen threshold of 0.05 to a GPD method.

## $threshold
## [1] 0.05
## 
## $nexc
## [1] 32
## 
## $conv
## [1] 0
## 
## $nllh
## [1] -74.3385
## 
## $mle
## [1] 0.01965532 0.60647468
## 
## $rate
## [1] 0.04238411
## 
## $se
## [1] 0.00558524 0.24858608

By using the POT approach, we built a model for high values of the negative log-returns where we obtain the Maximum Likelihood Estimates for the scale (sigma) and shape (ksi) parameters/coefficients : 0.01965532 and 0.60647468 [ARE THEY THE COEFF THEY ASKED TO REPORT ??], with Standard Errors being 0.00558524 and 0.24858608. [DOES THIS CORRESPONDS TO THE MEASURE OF UNCERTAINTY ??]

##          5% 
## -0.04455341